{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ck+_to_png.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMO8g3XVRrTdYGs6SuAbjbf"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "PWC1w1-0xJlE",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 128
        },
        "outputId": "0b5bbf50-be49-4e5d-869c-37466a4cc3c4"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KsbddzBi8gMQ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        },
        "outputId": "8fa60335-c88b-4e26-d229-a82d0a9369bd"
      },
      "source": [
        "! git clone https://github.com/ifp-uiuc/do-neural-networks-learn-faus-iccvw-2015.git"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'do-neural-networks-learn-faus-iccvw-2015'...\n",
            "remote: Enumerating objects: 265, done.\u001b[K\n",
            "remote: Total 265 (delta 0), reused 0 (delta 0), pack-reused 265\u001b[K\n",
            "Receiving objects: 100% (265/265), 232.63 KiB | 5.82 MiB/s, done.\n",
            "Resolving deltas: 100% (158/158), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J76fXHTw-FCU",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "! rm -rf ck+ && mkdir ck+\n",
        "! unzip -q '/content/drive/My Drive/cs230 project/dataset/ck+/extended-cohn-kanade-images.zip' -d /content/ck+\n",
        "! unzip -q '/content/drive/My Drive/cs230 project/dataset/ck+/FACS_labels.zip' -d /content/ck+\n",
        "! unzip -q '/content/drive/My Drive/cs230 project/dataset/ck+/Emotion_labels.zip' -d /content/ck+\n",
        "! mv '/content/ck+/Emotion'{,_labels}"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cJgl4RTOzaSu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# These folders give some processing issue, so we delete them\n",
        "! rm -rf ck+/cohn-kanade-images/S5*"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hNFoCurh6_j7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "! sed -i 's/96/48/g' do-neural-networks-learn-faus-iccvw-2015/data_scripts/make_ck_plus_dataset.py"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I9IUoYiGyyOx",
        "colab_type": "code",
        "outputId": "5aaee6f4-553f-458d-e7e8-0270cdff2895",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "! rm -rf ck-output && mkdir ck-output\n",
        "# keep only the first and last three images in each sequence\n",
        "! python2 do-neural-networks-learn-faus-iccvw-2015/data_scripts/make_ck_plus_dataset.py --input_path /content/ck+/ --save_path /content/ck-output"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "================================================================\n",
            "                Extended Cohn-Kanade Dataset Manager              \n",
            "================================================================\n",
            "\n",
            "Condensed Dataset detected.\n",
            "Removing it.\n",
            "Copying original dataset to new condensed dataset path.\n",
            "\n",
            "Condensing CK+ Dataset: \n",
            "255 empty sequences to be removed.\n",
            "\n",
            "Removing image sequence folders that have no label.\n",
            "There are 11 mismatched files.\n",
            "\n",
            "Removing empty label folders.\n",
            "\n",
            "Keeping only the first and last three images in each sequence.\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S005\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S010\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S011\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S014\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S022\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S026\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S028\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S029\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S032\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S034\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S035\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S037\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S042\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S044\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S045\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S046\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S050\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S051\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S052\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S053\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S054\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S055\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S056\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S057\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S058\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S059\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S060\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S061\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S062\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S063\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S064\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S065\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S066\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S067\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S068\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S069\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S070\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S071\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S072\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S073\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S074\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S075\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S076\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S077\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S078\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S079\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S080\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S081\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S082\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S083\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S084\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S085\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S086\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S087\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S088\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S089\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S090\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S091\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S092\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S093\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S094\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S095\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S096\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S097\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S098\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S099\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S100\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S101\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S102\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S105\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S106\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S107\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S108\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S109\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S110\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S111\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S112\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S113\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S114\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S115\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S116\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S117\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S119\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S122\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S124\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S125\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S126\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S127\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S128\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S129\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S130\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S131\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S132\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S133\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S134\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S135\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S136\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S137\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S138\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S139\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S147\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S148\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S149\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S151\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S154\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S155\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S156\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S157\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S158\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S160\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S895\n",
            "Processing:  /content/ck-output/cohn-kanade-images/S999\n",
            "\n",
            "Condensed CK+ Dataset Statistics: \n",
            "Total Number of Image Sequences: 308\n",
            "Total Number of Label Sequences: 327\n",
            "Number of sequences with correponding label .txt file: 327\n",
            "Total Number of Subjects: 112\n",
            "Number of image files: 1232\n",
            "\n",
            "Detecting and Cropping Faces\n",
            "/usr/local/lib/python2.7/dist-packages/skimage/transform/_warps.py:105: UserWarning: The default mode, 'constant', will be changed to 'reflect' in skimage 0.15.\n",
            "  warn(\"The default mode, 'constant', will be changed to 'reflect' in \"\n",
            "/usr/local/lib/python2.7/dist-packages/skimage/transform/_warps.py:110: UserWarning: Anti-aliasing will be enabled by default in skimage 0.15 to avoid aliasing artifacts when down-sampling images.\n",
            "  warn(\"Anti-aliasing will be enabled by default in skimage 0.15 to \"\n",
            "Missed Faces:  []\n",
            "\n",
            "Saving CK+ images and labels to .npy files.\n",
            "Subject: 0 - S005\n",
            "Subject: 1 - S010\n",
            "Subject: 2 - S011\n",
            "Subject: 3 - S014\n",
            "Subject: 4 - S022\n",
            "Subject: 5 - S026\n",
            "Subject: 6 - S028\n",
            "Subject: 7 - S029\n",
            "Subject: 8 - S032\n",
            "Subject: 9 - S034\n",
            "Subject: 10 - S035\n",
            "Subject: 11 - S037\n",
            "Subject: 12 - S042\n",
            "Subject: 13 - S044\n",
            "Subject: 14 - S045\n",
            "Subject: 15 - S046\n",
            "Subject: 16 - S050\n",
            "Subject: 17 - S051\n",
            "Subject: 18 - S052\n",
            "Subject: 19 - S053\n",
            "Subject: 20 - S054\n",
            "Subject: 21 - S055\n",
            "Subject: 22 - S056\n",
            "Subject: 23 - S057\n",
            "Subject: 24 - S058\n",
            "Subject: 25 - S059\n",
            "Subject: 26 - S060\n",
            "Subject: 27 - S061\n",
            "Subject: 28 - S062\n",
            "Subject: 29 - S063\n",
            "Subject: 30 - S064\n",
            "Subject: 31 - S065\n",
            "Subject: 32 - S066\n",
            "Subject: 33 - S067\n",
            "Subject: 34 - S068\n",
            "Subject: 35 - S069\n",
            "Subject: 36 - S070\n",
            "Subject: 37 - S071\n",
            "Subject: 38 - S072\n",
            "Subject: 39 - S073\n",
            "Subject: 40 - S074\n",
            "Subject: 41 - S075\n",
            "Subject: 42 - S076\n",
            "Subject: 43 - S077\n",
            "Subject: 44 - S078\n",
            "Subject: 45 - S079\n",
            "Subject: 46 - S080\n",
            "Subject: 47 - S081\n",
            "Subject: 48 - S082\n",
            "Subject: 49 - S083\n",
            "Subject: 50 - S084\n",
            "Subject: 51 - S085\n",
            "Subject: 52 - S086\n",
            "Subject: 53 - S087\n",
            "Subject: 54 - S088\n",
            "Subject: 55 - S089\n",
            "Subject: 56 - S090\n",
            "Subject: 57 - S091\n",
            "Subject: 58 - S092\n",
            "Subject: 59 - S093\n",
            "Subject: 60 - S094\n",
            "Subject: 61 - S095\n",
            "Subject: 62 - S096\n",
            "Subject: 63 - S097\n",
            "Subject: 64 - S098\n",
            "Subject: 65 - S099\n",
            "Subject: 66 - S100\n",
            "Subject: 67 - S101\n",
            "Subject: 68 - S102\n",
            "Subject: 69 - S105\n",
            "Subject: 70 - S106\n",
            "Subject: 71 - S107\n",
            "Subject: 72 - S108\n",
            "Subject: 73 - S109\n",
            "Subject: 74 - S110\n",
            "Subject: 75 - S111\n",
            "Subject: 76 - S112\n",
            "Subject: 77 - S113\n",
            "Subject: 78 - S114\n",
            "Subject: 79 - S115\n",
            "Subject: 80 - S116\n",
            "Subject: 81 - S117\n",
            "Subject: 82 - S119\n",
            "Subject: 83 - S122\n",
            "Subject: 84 - S124\n",
            "Subject: 85 - S125\n",
            "Subject: 86 - S126\n",
            "Subject: 87 - S127\n",
            "Subject: 88 - S128\n",
            "Subject: 89 - S129\n",
            "Subject: 90 - S130\n",
            "Subject: 91 - S131\n",
            "Subject: 92 - S132\n",
            "Subject: 93 - S133\n",
            "Subject: 94 - S134\n",
            "Subject: 95 - S135\n",
            "Subject: 96 - S136\n",
            "Subject: 97 - S137\n",
            "Subject: 98 - S138\n",
            "Subject: 99 - S139\n",
            "Subject: 100 - S147\n",
            "Subject: 101 - S148\n",
            "Subject: 102 - S149\n",
            "Subject: 103 - S151\n",
            "Subject: 104 - S154\n",
            "Subject: 105 - S155\n",
            "Subject: 106 - S156\n",
            "Subject: 107 - S157\n",
            "Subject: 108 - S158\n",
            "Subject: 109 - S160\n",
            "Subject: 110 - S895\n",
            "Subject: 111 - S999\n",
            "\n",
            "Making the folds.\n",
            "Subjs in fold 0: [  0  10  20  30  40  50  60  70  80  90 100 110]\n",
            "Subjs in fold 1: [  1  11  21  31  41  51  61  71  81  91 101 111]\n",
            "Subjs in fold 2: [  2  12  22  32  42  52  62  72  82  92 102]\n",
            "Subjs in fold 3: [  3  13  23  33  43  53  63  73  83  93 103]\n",
            "Subjs in fold 4: [  4  14  24  34  44  54  64  74  84  94 104]\n",
            "Subjs in fold 5: [  5  15  25  35  45  55  65  75  85  95 105]\n",
            "Subjs in fold 6: [  6  16  26  36  46  56  66  76  86  96 106]\n",
            "Subjs in fold 7: [  7  17  27  37  47  57  67  77  87  97 107]\n",
            "Subjs in fold 8: [  8  18  28  38  48  58  68  78  88  98 108]\n",
            "Subjs in fold 9: [  9  19  29  39  49  59  69  79  89  99 109]\n",
            "Number of samples/fold: [124 152 148 124 112 132 112 108 132  88]\n",
            "\n",
            "Successfully pre-processed the Extended Cohn-Kanade Dataset!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ssPdIwrJGVSv",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def reindex_labels(y8):\n",
        "    y = np.zeros(y8.shape, dtype=np.int8)\n",
        "    label_mapping = {0:6, 2:-1, 1:0, 3:1, 4:2, 5:3, 6:4, 7:5}\n",
        "    for i in range(0,len(y8)):\n",
        "        y[i] = label_mapping[y8[i]]\n",
        "\n",
        "    return y"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WNnIXqDyDL60",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "outputId": "a69ca768-c26b-4469-a5dc-a74c77e8fec3"
      },
      "source": [
        "y8[y8==2]"
      ],
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
              "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], dtype=int32)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7thKHuzr4enP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "\n",
        "X = np.load('/content/ck-output/npy_files/X.npy')\n",
        "y8 = np.load('/content/ck-output/npy_files/y.npy')\n",
        "y = reindex_labels(y8)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Oz92dXgDABoj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 290
        },
        "outputId": "d0f9f5fd-756d-40b3-ddc3-b8d30612d83e"
      },
      "source": [
        "#y8[y8==0]\n",
        "y[y==6]"
      ],
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n",
              "       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6],\n",
              "      dtype=int8)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GSH3CX8IE5yj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "outputId": "6305fe7a-79cb-4472-9555-f4d7f8969844"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "emotions = {0:'angry', 1:'disgust', 2:'fear', 3:'happy', 4:'sad', 5:'surprise', 6:'neutral'}\n",
        "\n",
        "for i in range(0,10):\n",
        "  plt.xlabel(emotions[y[i]])\n",
        "  plt.imshow(X[i].reshape(48,48),cmap='gray')\n",
        "  plt.figure()\n",
        "  break"
      ],
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Ze9/MTscYM1tYMTOmEYaa9TYyMlIIcCwAKcGBRSu1TQ4LFyqIhEWRJUuW9O2jRDwWhFSA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\nGygTX9hepgom85v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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZvgocTG4KF1v",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "! rm -rf ck-images && mkdir ck-images\n",
        "\n",
        "from os import mkdir\n",
        "for emotion in emotions:\n",
        "  mkdir(f'/content/ck-images/' + f'{emotion} ' + f'{emotions[emotion]}')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ojFKvNRXFA5G",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from PIL import Image\n",
        "\n",
        "count = 0\n",
        "for i in range(0,X.shape[0]):\n",
        "    if y[i] == -1:\n",
        "      continue\n",
        "    count_string = str(count).zfill(7)\n",
        "    fname = '/content/ck-images/' + f'{y[i]} ' + f'{emotions[y[i]]}/' + f'{emotions[y[i]]}-{count_string}.png'\n",
        "    img = Image.fromarray(X[i].reshape(48,48))\n",
        "    img.save(fname) \n",
        "    count += 1"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b-lZOMv4JCPC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "b0b9ffd8-82ef-46d8-9452-2a811175b71f"
      },
      "source": [
        "! cd ck-images && zip -r ck-plus.zip *"
      ],
      "execution_count": 92,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "  adding: 0 angry/ (stored 0%)\n",
            "  adding: 0 angry/angry-0000419.png (stored 0%)\n",
            "  adding: 0 angry/angry-0000955.png (stored 0%)\n",
            "  adding: 0 angry/angry-0000097.png (stored 0%)\n",
            "  adding: 0 angry/angry-0000611.png (stored 0%)\n",
            "  adding: 0 angry/angry-0001001.png (stored 0%)\n",
            "  adding: 0 angry/angry-0000118.png (stored 0%)\n",
            "  adding: 0 angry/angry-0001002.png (stored 0%)\n",
            "  adding: 0 angry/angry-0000098.png (stored 0%)\n",
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            "  adding: 0 angry/angry-0000799.png (stored 0%)\n",
            "  adding: 0 angry/angry-0000683.png (stored 0%)\n",
            "  adding: 0 angry/angry-0000711.png (stored 0%)\n",
            "  adding: 0 angry/angry-0000709.png (stored 0%)\n",
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            "  adding: 0 angry/angry-0000079.png (stored 0%)\n",
            "  adding: 0 angry/angry-0001139.png (stored 0%)\n",
            "  adding: 0 angry/angry-0000418.png (stored 0%)\n",
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            "  adding: 6 neutral/neutral-0001000.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001020.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000932.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000596.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000012.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000352.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000232.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000268.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000548.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000360.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000684.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000600.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000344.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001036.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000460.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000224.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000840.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001072.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000860.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000180.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000796.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001060.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000680.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001136.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000192.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000556.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000388.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001088.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000660.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000696.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000332.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001152.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000656.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000136.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000928.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000784.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000420.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000504.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000580.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000316.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000960.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000276.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000248.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001128.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001100.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000904.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001024.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000168.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000156.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000972.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000368.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001148.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001048.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000284.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000712.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000528.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000308.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000584.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000244.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000196.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000748.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000148.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000936.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000252.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000080.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001120.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000716.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000608.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000592.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001008.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000076.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000620.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000208.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000768.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000296.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000032.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000688.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000804.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000400.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001116.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000524.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000204.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000448.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001132.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000940.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000456.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001164.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000376.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001104.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000404.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001108.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000092.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000412.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000480.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001028.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000560.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000416.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001112.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000468.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001176.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000616.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000040.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000824.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000340.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000288.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000644.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000808.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001076.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000956.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000260.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000036.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001156.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000920.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000640.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000060.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000908.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000004.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000848.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000728.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001052.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000764.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000816.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000868.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000676.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000980.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0001175.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000408.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000564.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000720.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000380.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000016.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000924.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000968.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000948.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000160.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000184.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000484.png (stored 0%)\n",
            "  adding: 6 neutral/neutral-0000896.png (stored 0%)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pCsREeBHK2N7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "! mv ck-images/ck-plus.zip '/content/drive/My Drive/cs230 project/dataset/'"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}